“It is much easier after the event to sort the relevant from the irrelevant signals. After the event, of course, a signal is always crystal clear; we can now see what disaster it was signaling, since the disaster has occurred. But before the event it is obscure and pregnant with conflicting meanings. It comes to the observer embedded in an atmosphere of ‘noise’ i.e.; in the company of all sorts of information that is useless and irrelevant for predicting the particular disaster.”
-Roberta Wohlstetter Pearl Harbor: Warning and Decision (1962)
Forgive me for sounding redundant, but The Signal And The Noise is about the challenge in seeing the signal in the noise. The truth among the lies. The wheat from the chaff. The essential from the extraneous. The book is a document of human ingenuity and folly.
“This need of finding patterns, humans have more than any other animal,” I was told by Thomas Poggio, an MIT neuroscientist who studies how our brains process information.”Recognizing objects in difficult situations means generalizing. A newborn baby can recognize the basic pattern of a face. It has been learned by evolution, not by the individual.”
The problem, Poggio says, is that these evolutionary instincts sometimes lead us to see patterns that aren’t there. “People have been doing that all the time,” Poggio said. “Finding patterns in random noise.”
Nate Silver is a statistical journalist who makes predictions in sports and politics for media outlets like ESPN and The New York Times. Here, he examines the successes and failures of many industries and pastimes that are on the forefront of prediction making; including meteorology, chess, poker, epidemiology, political elections, sports, and the stock market.
The tone of the book is cautiously optimistic because the author is weary of the notion that more data makes for better predictions. Instead, he contends that more data is mostly more noise for the truth to be buried in. Things might be worse than ever, considering that humanity is generating around 2.5 quintillion bytes of data each day, exponentially more than ever before.
The human brain is quite remarkable; it can store perhaps three terabytes of information. And yet that is only about one-millionth of the information that IBM says is now produced in the world each day. So we have to be terribly selective about the information we choose to remember.
Meanwhile, if the quantity of information is increasing by 2.5 quintillion bytes per day, the amount of useful information almost certainly isn’t. Most of it is just noise, and the noise is increasing faster than the signal. There are so many hypotheses to test, so many data sets to mine – but a relatively constant amount of objective truth.
Information is no longer a scarce commodity; we have more of it than we know what to do with. But relatively little of it is useful. We perceive it selectively, subjectively, and without much self-regard for the distortions that it causes. We think we want information when we really want knowledge.
He sees the intellectual history of prediction science as a pendulum swinging back and forth between Laplace’s Demon and Heisenberg’s Uncertainty Principal. In other words, between incautious and hedonistic optimism, and the humbling realization that the future is unwritten and so cannot be foreseen.
Our views on how predictable the world is have waxed and waned over the years. One simple measure of it is the number of times the words ‘predictable’ and ‘unpredictable’ are used in academic journals. At the dawn of the twentieth century, the two words were used almost exactly as often as one another. The Great Depression and the Second World War capitulated ‘unpredictable’ into the dominant position. As the world healed from these crises, ‘predictable’ came back into fashion, its usage peaking in the 1970s. ‘Unpredictable’ has been on the rise again in recent years.
Excerpt from the book on FiveThirtyEight.com
Bob Lefsetz on Nate Silver
What the professionals had to say—Wall Street Journal book review
Buy from Amazon
The Signal and the Noise: Why So Many Predictions Fail but Some Don’t
Interesting anecdotes and new vocabulary
Laplace’s Demon — A hypothetical omniscient beast that was 18th century mathematician/astronomer Pierre-Simon Laplace’s rationalization for a predictable universe that could be comprehensible to humanity if only they had enough information.
Heisenberg’s Uncertainty Principal — “How can you predict where something is going to go when you don’t know where it is in the first place? You can’t.”
Schoolhouse Blizzard 1888 —a blizzard hit that unexpectedly in the American Great Plains on January 12, 1888 on a relatively warm day. The temperature dropped almost 30 degrees in a few hours and a blinding blizzard caught people unaware. Hundreds of children, leaving school as the blizzard hit, died of hypothermia on their way home.
Lisbon Earthquake 1775 — “No type of catastrophe is more jarring to our sense of order than an earthquake. They quite literally shake our foundations. Whereas hurricanes descend upon us from the heavens and have sometimes been associated with metaphors for God’s providence, earthquakes come from deep underneath the surface and are more often taken to be signs of His wrath, indifference, or nonexistence. (The Lisbon Earthquake of 1755 was a major spark for the development of secular philosophy.) pg. 145”
Brownian noise — noise produced by the motion of particles, like a waterfall. “If you listen to true white noise, which is produced by random bursts of sounds over a uniform distribution of frequencies, it is sibilant and somewhat abrasive. The type of noise associated with complex systems, called Brownian noise, is more soothing and sounds almost like rushing water. pg.173”
Livingston Survey — an organized effort to predict economic variables like GDP.
1976 Swine Flu Outbreak — A political disaster reminiscent of the current Ebola scare. The H1N1 strand responsible for the Spanish Flu of 1918-20 and 50 million deaths kills one Army lieutenant at Fort Dix. A series of dire predictions soon followed. Gerald Ford;s secretary of health, F. David Mathews, predicted that one million Americans would die. So Ford took the resolute step of asking Congress to authorize some 200 million does of vaccine, and ordered a mass vaccination program, the first of its kind since Polio. Overwhelming majorities in both houses approved his plans at a cost of $180 million. The next flu season came and no cases of H1N1 were reported outside of Fort Dix the previous year. The Ford Administration doubled down, releasing a series of ominous public service announcements that served more to terrify the population of the government and the vaccine itself than of the flu.
anosognosia — When a possibility is unfamiliar to us, we don’t even think about it.
sibilant — (of a speech sound) sounded with a hissing.